Method of reducing noise in volume imaging

ABSTRACT

In a method of visualizing a three-dimensional volume image data set ( 1 ), a two-dimensional image ( 15 ) is formed by projecting volume image data on a projection plane in that for each pixel ( 16 ) there is determined an intensity value which corresponds to the maximum value or minimum value of the mean intensity along a projection path ( 17 ) through the imaged volume and associated with the relevant pixel. In order to determine the mean intensity, averaging is performed over a plurality of intensity values which neighbor one another along the projection path ( 17 ). In order to achieve effective noise suppression as well as adequate along image contrast , averaging is performed over at least partly overlapping interval ( 18  to  22 ) along the projection path ( 17 ). The method offer the advantage that the user can choose the width of the averaging interval as an additional free parameter, so that image contrast and background noise can be influenced independently.

The invention relates to a method of visualizing a three-dimensionalvolume image data set which contains a plurality of intensity values ona discrete spatial grid, in which method a two-dimensional image isformed by projecting the volume image data on a projection plane in thatfor each pixel there is determined an intensity value which correspondsto the maximum value or minimum value of the mean intensity along aprojection path which extends through the imaged volume and isassociated with the relevant pixel, the mean intensity being calculatedby averaging over a plurality of intensity values of the volume imagedata set which neighbor one another along the projection path. Theinvention also relates to an imaging diagnostic apparatus, notably a CTapparatus or an MR apparatus, and to a computer program for carrying outthe method in accordance with the invention.

Optimum visualization of image data is of crucial importance for medicalapplications, because such applications concern the formation ofdiagnostic images which are produced, for example, by means of computedtomography (CT) or by means of magnetic resonance tomography (MR). Theobject is to make the characteristic anatomical structures inside apatient to be examined recognizable on the basis of a two-dimensionalrendition. In medical imaging volume image data of a region of interestof the patient to be examined is reconstructed from the absorption ofthe X-rays (CT) or from the spin resonance signals (MR). The resultantimage data set contains intensity values for each point of a discretespatial grid. This data set, consisting of equidistant, so-calledvoxels, is further processed by means of suitable methods in thereconstruction unit of the relevant diagnostic imaging apparatus, thatis, so as to visualize the anatomical structures, consisting ofdifferent types of tissue, on the basis of the different imageintensities.

The quality of the visualization is decisively dependent on the methodused to transform the three-dimensional volume image data into atwo-dimensional rendition. It is important that no crucial imageinformation is lost by the reduction from three to two dimensions.

There are various known methods of forming a two-dimensional image byprojecting the volume image data on a projection plane. Each pixel ofthe projection image is then associated with a rectilinear projectionpath which extends through the imaged volume and is orientedperpendicularly to the image plane. For each pixel an intensity value isdetermined by evaluation of the intensity variation along the relevantprojection path. In the simplest case the intensity values of the volumeimage data set are averaged along each individual projection path. Theintensity values are then summed and subsequently divided by the numberof voxels situated along the relevant projection path. This approachoffers the advantage that background noise which is inevitably presentin real image data is effectively suppressed as a result of theaveraging. This method, which is also referred to as the Collapsed View(CV) method, has the unacceptable side effect that the image contrast isreduced to such an extent that only objects exhibiting extremedifferences in intensity can still be recognized in the resultant image.Depending on the relevant application, the image structures of interestare characterized by particularly high or particularly low intensityvalues. CT angiography, for example, utilizes the fact that the bloodpresent in the vessels being examined yields a higher voxel intensitythan the other organs of the imaged anatomy. In these cases the use ofthe so-called Maximum (Minimum) Intensity Projection (MIP and mIP,respectively) method has become customary for generating two-dimensionalprojection images. The intensity value which corresponds to the maximumvalue or the minimum value of the voxel intensity along the projectionpath associated with the relevant pixel is then associated with eachpixel of the two-dimensional projection image. The MIP or mIP method isvery fast and reliably produces the desired image information uponreduction of the image data to two dimensions. However, it is also knownthat this method tends to give rise to artifacts which cannot be readilyrecognized in the resultant image. Furthermore, the MIP or mIP methodemphasizes the background signal (noise) so that in given circumstancesindividual image objects will not be clearly visualized in the resultantimage.

In order to overcome said drawbacks, Thelissen proposes a so-calledMaximum Average Projection (MAP) method in which averaging over aselectable number of voxels which succeed one another along the relevantprojection path is performed prior to the determination of the maximumintensity value (Guillaume R. P. Thelissen, “Maximum Average Projection(MAP): A fast and robust way to visualize 3-dimensional MR data-sets”,Proceedings of the ISMRM 1998, 2105). The known method at the same timeeffectively suppresses the background noise and the desired contrastenhancement is achieved as in the MIP method. Since it is possible toselect the number of successive voxels along the relevant projectionpath over which averaging takes place in accordance with the knownmethod, the quality of the two-dimensional projection image isadjustable. For adaptation to the relevant image noise the user canchoose this value to be such that an as optimum as possible compromiseis obtained between noise and image contrast.

The main drawback of the known method resides in the fact that as beforea contradiction continues to exist between the desire for an as weak aspossible image noise and an as high as possible image contrast.According to the known method the volume image data set is subdividedinto mutually independent image slices prior to the determination of themaximum intensity values, the thickness of said slices being dependenton the number of voxels over which the averaging is carried out. Thepreviously mentioned Collapsed View (CV) method is applied to a givenextent to each of these image slices in order to calculate the meanintensity values. These mean intensity values are compared with oneanother along the relevant projection path in order to determine themaximum value for the resultant projection image. The thicker the imageslices are, that is, the larger the number of voxels over whichaveraging takes place, the smaller the number of mean intensity valuesevaluated during the projection will be. When a particularly strongnoise suppression is desirable, averaging should take place overintervals which are as large as possible. However, this has an adverseeffect on the image contrast, because the projection is then based on acorrespondingly smaller number of mean intensity values. It is alsoparticularly disadvantageous that in the known method image informationmay be lost when the structures imaged are situated at the boundarybetween neighboring averaging intervals. This may give rise to imageartefacts so that the known method becomes rather problematic, that is,notably for diagnostic imaging.

Considering the foregoing, it is an object of the present invention toimprove the known method to such an extent that an as effective aspossible noise suppression takes place without giving rise, if possible,to loss of image information.

This object is achieved on the basis of a method of the kind set forthin that averaging is carried out over at least partly overlappingintervals along the projection path.

An advantage of the method in accordance with the invention resides inthe fact that, because of their partial overlapping, the averaging zonesare larger than in the known method, so that overall the noisesuppression is more effective. A further advantage consists in that, asopposed to the known method, the number of mean intensity valuesevaluated during the projection is not limited by the selected width ofthe averaging interval. Because the averaging intervals overlap at leastpartly, the number of intensity values over which the averagingoperation is carried out can be selected independently of the number ofmean values. Because the density of the mean intensity values along theprojection path may be significantly higher, the desired maximum orminimum intensity value will be determined with an accuracy which issignificantly higher than that achieved in the known method. Moreover,no undesirable image artefacts occur, not even when the width of theaveraging interval is larger than the image structures of interest.

In an advantageous further version of the method in accordance with theinvention the averaging is carried out by convolution of the intensityvariation along the projection path with a weighting function which hasa selectable width which is larger than the distance in space betweentwo neighboring data points of the volume image data set. Such aconvolution provides smoothing of the intensity variation along theprojection path. The width of the smoothing function can then beselected at will as an independent parameter. The method in accordancewith the invention can be carried out in such a manner that, despite theaveraging, the overall number of intensity values on which theprojection is based is maintained. When a suitable weighting function ischosen for the convolution, for example, a Gaussian function, the maximaor minima of the intensity variation will be maintained even when theaveraging interval is significantly larger than the image structures tobe imaged.

It has been found that for a practical application of the method inaccordance with the invention it is effective to carry out the averagingover intervals which overlap each time by one half. Using the samenumber of mean intensity values which are evaluated during theprojection, the width of the averaging interval is then twice as largeas in the known method. The noise suppression is thus significantlyimproved whereas the image contrast is not noticeably degraded.

A CT apparatus or an MR apparatus or other imaging diagnostic apparatusis suitable for carrying out the method in accordance with theinvention, the apparatus which includes an imaging unit for theacquisition of coarse data of an object to be examined and also includesa program-controlled reconstruction unit which reconstructs volume imagedata from the coarse data, the volume image data consisting of aplurality of intensity values on a discrete spatial grid, and also formsa two-dimensional image therefrom by projecting the volume image data ona projection plane, characterized in that projection of the volume imagedata is carried out by the reconstruction unit in such a manner that foreach pixel there is determined an intensity value which corresponds tothe maximum value or minimum value of the mean intensity along aprojection path which extends through the imaged volume and isassociated with the relevant pixel, the mean intensity being calculatedby averaging over at least partly overlapping intervals along theprojection path. The method in accordance with the invention can beadvantageously implemented, that is, without necessitating specialadaptations of the hardware, in conventional diagnostic apparatus inclinical use, since only the reconstruction unit is provided with asuitable program for the visualization in accordance with the invention.

A computer program is suitable for this purpose, the computer programcharacterized in that it forms a two-dimensional image from athree-dimensional volume image data set, consisting of a plurality ofintensity values on a discrete spatial grid, by projecting the volumeimage data on a projection plane in that for each pixel it determines anintensity value which corresponds to the maximum value or minimum valueof the mean intensity along a projection path which extends through theimaged volume and is associated with the relevant pixel, the meanintensity being calculated by averaging over at least partly overlappingintervals along the projection path. The computer program alsocharacterized in that it performs the averaging by convolution of theintensity variation along the projection path with a weighting functionwhich has a width which can be selected by the user and is larger thanthe distance in space between two neighboring data points of the volumeimage data set. A computer program of this kind can be made available tothe users of conventional imaging diagnostic apparatus on a suitabledata carrier, for example, a disc or a CD-ROM, or can be offered fordownloading via a public data network (the Internet).

DRAWINGS

Embodiments of the invention will be described in detail hereinafterwith reference to the Figures. Therein:

FIG. 1 illustrates the projection method in accordance with theinvention;

FIG. 2 shows the averaging with averaging intervals which overlap by onehalf, and

FIG. 3 shows a CT apparatus in accordance with the invention.

DESCRIPTION

FIG. 1 shows a three-dimensional volume image data set which is denotedby the reference numeral 1. The examination volume shown has anapproximately cubic shape and contains a blood vessel 2 which ischaracterized by a particularly high image intensity. The volume imagedata set 1 consists of twelve parallel slice images 3 to 14. Each of theslice images 3 to 14 consists of a two-dimensional matrix of intensityvalues. In order to visualize the volume image data set 1, atwo-dimensional image 15 is formed by projecting the volume image dataon the plane of the projection image 15. For each pixel 16 there isdetermined an intensity value which corresponds to the maximum orminimum value of the mean intensity along a projection path 17 whichextends through the imaged volume and is associated with the relevantpixel 16. The plane of the projection image 15 is oriented parallel tothe slice images 3 to 14 in FIG. 1. The projection path 17 extendsrectilinearly through the volume image data set and is orientedperpendicularly to the projection plane. For the determination of theintensity value for the pixel 16 first the mean intensities within thevolume image data set 1 are calculated by averaging over a plurality ofintensity values which neighbor one another along the projection path17. FIG. 1 shows five averaging intervals 18 to 21 which partly overlapone another in conformity with the invention. For each of the averagingintervals 18 to 21 there is determined a mean intensity value. Thus,five mean values are compared with one another in order to find themaximum or minimum value of the mean intensity. For the interval 18 amean intensity value is calculated for the corresponding point on theprojection path 17 by averaging over the slice images 3, 4, 5 and 6. Themean intensity value for the next interval 19 is obtained by averagingover the slices 5, 6, 7 and 8. Thus, in accordance with the inventionthe slices 5 and 6 are used for the determination of the mean value inthe interval 18 and in the interval 19. The method in accordance withthe invention yields a planar image 22 of the blood vessel 2.

FIG. 2 shows various possibilities for the averaging by means ofaveraging intervals which overlap each time by one half, that is, in thecase of a volume image data set consisting of ten slices. In the upperdiagram averaging takes place over the entire thickness 23 of theexamination zone. This approach corresponds to the previously describedCollapsed View (CV) method. In the diagram shown therebelow averagingtakes place over two intervals 24 and 25 which overlap in the centralthird part of the overall examination volume. Three, four and nine meanintensity values, respectively, are determined in the diagrams which areshown therebelow. In the case of nine averaging operations the width ofthe averaging interval 26 corresponds exactly to two image slices. Inthe diagram shown at the very bottom no averaging takes place. In thatcase the projection takes place in conformity with the customary MIP ormIP method.

The CT apparatus as shown in FIG. 3 consists of a portal 27 on which anX-ray source 28 rotates about a patient table 29 and a patient 30arranged thereon. On the portal there is also mounted a radiationdetector 31 which faces the X-ray source 28 and also rotates about thepatient 30. The radiation detector 31 detects the attenuation of anX-ray beam emitted by the X-ray source 28. The X-ray intensity isfurther processed and digitized by a measuring device 32. This data isthen applied to a microcomputer 33 which reconstructs volume image datafrom the X-ray absorption data. The computer 33 is programmed in such amanner that in conformity with the invention it forms a two-dimensionalimage 15 from the reconstructed volume image data, said image beingdisplayed on the display unit of the computer 33.

1. A method of visualizing a three-dimensional volume image data set (1)which contains a plurality of intensity values on a discrete spatialgrid, in which method a two-dimensional image (15) is formed byprojecting the volume image data on a projection plane in that for eachpixel (16) there is determined an intensity value which corresponds tothe maximum value or minimum value of the mean intensity along aprojection path (17) which is associated with the relevant pixel andextends through the imaged volume, the mean intensity being calculatedby averaging over a plurality of intensity values of the volume imagedata set (1) which neighbor one another along the projection path,characterized in that the averaging is carried out over at least partlyoverlapping intervals (18 to 22) along the projection path (17).
 2. Amethod as claimed in claim 1, characterized in that the averaging iscarried out by convolution of the intensity variation along theprojection path with a weighting function which has a selectable widthwhich is larger than the distance in space between two neighboring datapoints of the volume image data set.
 3. A method as claimed in claim 1,characterized in that the intervals over which the averaging isperformed overlap each time by one half.
 4. An imaging diagnosticapparatus, notably a CT apparatus or an MR apparatus, for carrying outthe method claimed in claim 1, which apparatus includes an imaging unit(27, 28, 31, 32) for the acquisition of coarse data of an object (30) tobe examined and also includes a program-controlled reconstruction unit(33) which reconstructs volume image data from the coarse data, saidvolume image data consisting of a plurality of intensity values on adiscrete spatial grid, and also forms a two-dimensional image (15)therefrom by projecting the volume image data on a projection plane,characterized in that projection of the volume image data is carried outby the reconstruction unit (33) in such a manner that for each pixel(16) there is determined an intensity value which corresponds to themaximum value or minimum value of the mean intensity along a projectionpath (17) which extends through the imaged volume and is associated withthe relevant pixel, the mean intensity being calculated by averagingover at least partly overlapping intervals (18 to 22) along theprojection path.
 5. A computer program for carrying out the methodclaimed in claim 1, characterized in that it forms a two-dimensionalimage (15) from a three-dimensional volume image data set (1),consisting of a plurality of intensity values on a discrete spatialgrid, by projecting the volume image data on a projection plane in thatfor each pixel (16) it determines an intensity value which correspondsto the maximum value or minimum value of the mean intensity along aprojection path (17) which extends through the imaged volume and isassociated with the relevant pixel, the mean intensity being calculatedby averaging over at least partly overlapping intervals (18 to 22) alongthe projection path (17).
 6. A computer program as claimed in claim 5,characterized in that it performs the averaging by convolution of theintensity variation along the projection path with a weighting functionwhich has a width which can be selected by the user and is larger thanthe distance in space between two neighboring data points of the volumeimage data set.